When attempting to fit a curve to a set of data points, producing a curve with high curvature which fits the data points well, but does not model the underlying function well, its shape being distorted by the noise inherent in the data.See also, Neural Networks .

In statistics and machine learning, overfitting occurs when a statistical model describes random error or noise instead of the underlying relationship. Overfitting generally occurs when a model is excessively complex, such as having too many parameters relative to the number of observations. A model that has been overfit will generally have poor predictive performance, as it can exaggerate minor fluctuations in the data.